Multiple-input multiple-output (MIMO) communications systems use multiple antennas at the transmitter and receiver to provide increased throughput through a communication channel. In theory, the available capacity of a radio channel can increase linearly with the minimum number of antennas at either the transmitter or receiver. Unfortunately, complex signal processing is generally required in order to obtain the increased throughput.
One optimal solution for MIMO communications uses so-called pre-coding or beam forming and the so-called water-filling method to assign transmission power levels. The water-filling method uses knowledge of the channel response to determine optimal transmission power assignments to the transmit antennas. Channel response information is not directly available to the transmitter. Furthermore, the channel response can be actively changing. Therefore, the receiver typically estimates the channel response and feeds back the channel response information to the transmitter. Delays or errors in obtaining the channel response information (also referred to as channel state), however, reduce the performance of this approach. The estimation of channel response and feedback of channel state information also adds complexity to the overall communication systems.
A less complex alternative avoids requiring knowledge of the channel state at the transmitter. In the absence of channel state information at the transmitter, an optimal technique is for the transmitter to assign the same power to each antenna. The receiver can use maximum likelihood detection to maximize the performance. Unfortunately, maximum likelihood decoding is complex, and the complexity increases exponentially with the number of antennas.